Just about every industry these days makes use of data. This is because data provides hard, real, and relevant insights into both business practices and customer behaviors that can help transform industry for the better. The more skilled you are at utilizing data, the more opportunities you’ll have in the modern business world.
But data can be nebulous and complicated. Not only will you need a comprehensive plan for collecting data but you’ll also need the ability to manage and analyze that data. From data analytics to the common technologies it requires, there is a lot to know about data in today’s job market. The more you build this knowledge, the better prepared you’ll be to land your dream opportunities.
So without further ado, these are the data skills you’ll need in today’s economy.
Digital Literacy
Let’s start with the most straightforward and the broadest of the data skills you’ll need. Digital literacy is one of the biggest keys to success in the global economy of today. This is because every industry now employs technology and data management systems to maximize the efficiency of its practices.
In fact, strong digital literacy can lead to success across industries and careers. You can’t underestimate the value of being able to work with diverse software programs and business hardware. To future-proof your career, general technological fluency is a must.
Among the many technologies you should be familiar with are the following:
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Document creation and processing software
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Image editing tools
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Video creation, editing, and file management processes
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Data storage and management systems
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These tools serve as a strong basis for being digitally literate for the modern business world. However, the more understanding and control you have over data tools, the more potential you’ll have in the workplace.
Data Analytics
Data analytics is its own skillset. Having any level of expertise in this field will allow you to help businesses transform for the modern economy, providing them unprecedented transparency, insight, and agility. As we continue to navigate a pandemic-altered economy, these skills are a must for any business looking to maximize its revenue potential.
Data analytics is strictly the data side of business analytics, or the practice of using data to draw out actionable information regarding how to improve a business. Business analytics allows a company to structure raw data into something they can work with. That might mean predictive analysis of demand or customer profile creation through big data evaluation.
Big data offers a competitive edge to any business that can utilize it. For instance, big data is now impacting the real estate industry by revolutionizing personalization and buyer targeting. Becoming proficient in this field will require skills in:
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Structured Query Language (SQL) to make efficient use of databases
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Communication
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Data visualization
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Statistical visualization
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Probability and statistics
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Develop skills in data analytics to maximize the potential of any business you work with.
Programming
Next, you’ll want to consider honing your programming expertise. While not every data expert will need to know how to program, it certainly helps. Working with data means working with databases, queries, and algorithms. If you know a language like SQL, you’ll be able to seamlessly draw out the data you’re looking for.
Meanwhile, statistical programming allows you to automate advanced analyses that would not be possible in Excel or other common data entry programs. The more proficient you are in these programming languages, the better you’ll be able to streamline your data for easy analysis.
Expand your professional potential by learning statistical programming languages. These are some of the most in-demand languages to learn when it comes to data analytics:
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SQL
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R
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Python
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Java
AI and Machine Learning
Finally, we would be remiss not to mention the role of artificial intelligence and machine learning in the market now, especially as these tools advance into the future. AI is powering a revolution in data analysis and automation. Machine Learning, a subfield of AI in which algorithms adapt and learn from the data they assess, is going even further.
Automated Machine Learning (autoML) has become vital in helping businesses improve their models at every level. It concludes the data and then tests ideal solutions all on its own until it produces a recommended best. If you can help produce such a tool for a company, you’ll have your pick of jobs when it comes time to apply.
But AI, ML, and automating these tools can be particularly difficult. To advance in the field, you’ll need to become an expert in skills like:
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Computer science
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Software engineering
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ML algorithm selection and cross-validation
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Advanced mathematics
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If going that far isn’t your speed, at least maintain enthusiasm for the potential of AI and ML in data science. Enthusiasm, after all, is one of the most important factors companies look for when hiring a data scientist.
Developing a Data-Driven Skillset
These days, data is everything. The global market for big data analytics is expected to reach $105.8 billion in value by 2027 because of the benefits analytics offers the businesses that utilize it. To earn your share of this growth industry, you’ll need to start developing a data-driven skillset now. Start with digital literacy, then expand into programming languages and computer engineering.
With data as high in demand as it is, a data career is one of limitless opportunities. Develop your skills now to make the most of these opportunities.
